{"title":"基于局部多项式调试率的半参数nhpp软件可靠性建模","authors":"Siqiao Li, T. Dohi, H. Okamura","doi":"10.13052/jrss0974-8024.15215","DOIUrl":null,"url":null,"abstract":"In this paper, we propose a new non-homogeneous Poisson process (NHPP) based software reliability model (SRM), where the software debug rate is given by a local polynomial function. The main feature of this semi-parametric SRM is to control the goodness-of-fit by changing the polynomial degree. Numerical examples with 16 actual software development project data are devoted to comparing our SRM with the well-known existing NHPP-based SRMs in terms of goodness-of-fit and predictive performances.","PeriodicalId":42526,"journal":{"name":"Journal of Reliability and Statistical Studies","volume":null,"pages":null},"PeriodicalIF":0.9000,"publicationDate":"2023-04-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A Semi-parametric NHPP-based Software Reliability Modeling with Local Polynomial Debug Rate\",\"authors\":\"Siqiao Li, T. Dohi, H. Okamura\",\"doi\":\"10.13052/jrss0974-8024.15215\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, we propose a new non-homogeneous Poisson process (NHPP) based software reliability model (SRM), where the software debug rate is given by a local polynomial function. The main feature of this semi-parametric SRM is to control the goodness-of-fit by changing the polynomial degree. Numerical examples with 16 actual software development project data are devoted to comparing our SRM with the well-known existing NHPP-based SRMs in terms of goodness-of-fit and predictive performances.\",\"PeriodicalId\":42526,\"journal\":{\"name\":\"Journal of Reliability and Statistical Studies\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2023-04-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Reliability and Statistical Studies\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.13052/jrss0974-8024.15215\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"STATISTICS & PROBABILITY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Reliability and Statistical Studies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.13052/jrss0974-8024.15215","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"STATISTICS & PROBABILITY","Score":null,"Total":0}
A Semi-parametric NHPP-based Software Reliability Modeling with Local Polynomial Debug Rate
In this paper, we propose a new non-homogeneous Poisson process (NHPP) based software reliability model (SRM), where the software debug rate is given by a local polynomial function. The main feature of this semi-parametric SRM is to control the goodness-of-fit by changing the polynomial degree. Numerical examples with 16 actual software development project data are devoted to comparing our SRM with the well-known existing NHPP-based SRMs in terms of goodness-of-fit and predictive performances.
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